Embeddings are vectors of floating points representing, in a high-dimensional latent space, the information contained in a text, an image or an audio.

These vectors carry a lot of information about the original data, they serve as crucial tools for machine learning models to make predictions, find similar objects and perform semantic search.

Join me in this talk where we will discover how embeddings can be generated using open-source models and what we can do with them.